Growth, Female Size, and Sex Ratio Variability in American Eel of Different Origins in Both Controlled Conditions and the Wild: Implications for Stocking Programs
Bibliographic record
Abstract
Abstract Freshwater eels Anguilla spp. are declining worldwide, and a major challenge is understanding why these panmictic species show contrasting patterns of intraspecific phenotypic variation and recruitment. We present results on studies of the American Eel A. rostrata to understand and discriminate the effects of origin and plasticity on growth and sex determination. We considered two separate growth and one length‐at‐age data sets. The first growth data set originated from a 34‐month rearing experiment starting from the glass eel life stage to test the effects of origin, salinity, and density on growth and sex determination. The second growth data set originated from a shorter rearing experiment of 18 months starting at the yellow eel stage (around 3 years old) and compared transplanted individuals in Lake Ontario (LO) with natural migrants to the LO area. The third data set compared transplanted individuals in LO sampled by electrofishing with naturally migrating individuals. Sex ratios were identical for all origins and treatments in the long‐term growth experiment (34–35% females). While male size distribution had little variability, certain female groups had a large variation in growth and presented fast‐ and slow‐growing clusters. On the other hand, both cases of natural migrants to the LO area were consistent with being only slow‐growing females. We found that wild individuals rearing in the LO area were nearly exclusively transplanted individuals and that males, as well as fast‐growing females, were present. Even though the entire species is panmictic, these results support a role for spatially varying selection in explaining the phenotypic variation observed among regions and among individuals of the same region, and such factors must be considered for any successful management strategies of American Eel. Received December 17, 2013; accepted September 29, 2014
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".